Abstract
A model capable of predicting pore characteristics and rendering representative images of porous materials is described. A long-term goal is to discriminate between open and closed porosities. Aerogels are modeled by intersecting excursion sets of two independent Gaussian random fields. The parameters of these fields are obtained by matching small-angle neutron scattering data with the scattering function for the model. The chord-length probability density functions are then computed for the model, which contain partial clustering information for the aerogels. Visualizations of this model are performed and compared to electron microscopy images and gas adsorption pore size distributions.
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